Hierarchical representations of transportation networks should provide a better understanding of mobility patterns and the underlying structures at various abstraction levels. A hierarchical graph-based model allows representing moving objects and trajectories according to multiple spatial, temporal and semantic scales. The latter model is implemented here in a Neo4j graph database (version 4.4.0) and experimented with historical maritime data covering Brittany Bay in France
Mobility data has increasingly grown in volume over the past decade as loc- alisation technologies ...
Learning more about people mobility is an important task for official decision makers and urban plan...
The explosion of personal positioning devices like GPS-enabled smartphones has enabled the collectio...
Existing data models for moving objects in networks are often limited by flexibly controlling the gr...
It is difficult to visualize and extract meaningful patterns from massive trajectory data. One of th...
This paper proposes a graph-based approach to representing spatio-temporal trajectory data that allo...
This paper proposes a graph-based approach to representing spatio-temporal trajectory data that allo...
A transportation network is a complex system that exhibits the properties of self-organization and e...
This paper introduces a prospective study of the potential of spatio-temporal graphs (ST-graphs) and...
A transportation network is a complex system that exhibits the properties of self-organization and e...
Human Mobility has attracted attentions from different fields of studies such as epidemic modeling, ...
Public transport networks constitute critical infrastructure in urban systems. Public transport netw...
Cities are complex, dynamic and ever-evolving. We need to understand how these cities work in order ...
The mining of human mobility can be exploited to support the design of traffic planning, route recom...
http://www.uk.sagepub.com/books/Book234882The first section discusses the static dimension (structur...
Mobility data has increasingly grown in volume over the past decade as loc- alisation technologies ...
Learning more about people mobility is an important task for official decision makers and urban plan...
The explosion of personal positioning devices like GPS-enabled smartphones has enabled the collectio...
Existing data models for moving objects in networks are often limited by flexibly controlling the gr...
It is difficult to visualize and extract meaningful patterns from massive trajectory data. One of th...
This paper proposes a graph-based approach to representing spatio-temporal trajectory data that allo...
This paper proposes a graph-based approach to representing spatio-temporal trajectory data that allo...
A transportation network is a complex system that exhibits the properties of self-organization and e...
This paper introduces a prospective study of the potential of spatio-temporal graphs (ST-graphs) and...
A transportation network is a complex system that exhibits the properties of self-organization and e...
Human Mobility has attracted attentions from different fields of studies such as epidemic modeling, ...
Public transport networks constitute critical infrastructure in urban systems. Public transport netw...
Cities are complex, dynamic and ever-evolving. We need to understand how these cities work in order ...
The mining of human mobility can be exploited to support the design of traffic planning, route recom...
http://www.uk.sagepub.com/books/Book234882The first section discusses the static dimension (structur...
Mobility data has increasingly grown in volume over the past decade as loc- alisation technologies ...
Learning more about people mobility is an important task for official decision makers and urban plan...
The explosion of personal positioning devices like GPS-enabled smartphones has enabled the collectio...